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ThesisItem Open Access Development of a suitable model for ascertaining the growth and egg production in quails(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 1991) John Thomas, M; KAU; George, K CAn investigation was carried out into the growth and egg production aspect of Japanese quails at the Kerala Agricultural University Poultry Farm, Mannuthy on 1st February, 1989 with the following objectives. 1. to find a suitable relationship between age and body weight. 2. to investigate the" trend of egg production in quails through suitable mathematical models. ,3. to study the impact of climate parameters (temperature, ; , humidity) on egg production in quails. The birds were reared under uniform feed formula and ^identical management practices (recommended by Kerala Agricul tural University Package of Practices). The investigation mainly depended on' data consisting of weekly body weights of -ii^-dividual birds, daily egg production of birds (beginning from age at sexual maturity) and daily climatological para meters (temperature and humidity) from beginning till the end of experiment of 30th September, 1989. Mathematical models such as linear, quadratic, exponential, .Von-Bertalanffy, modified exponential, logistic and Gompertz were fitted for the purpose using body weights of ) individual birds as well as average body weights over twelve weeks and the fitted models were compared using coefficient of 2 determination (r ) and standard error of estimate(s). Mathematical models such as linear, exponentialf parabolic exponential, inverse polynomial. Gamma function. Gamma-type functic^n, quadratic function, quadratic function in logari'thmic scale, quadratic-cum-log, emperical and linear hyperbolic functions were fitted for the development of suitable models for ascertaining egg production using total weekly, fortnightly egg production, hen housed and hen day egg production and fitted models were compared using Furnival index, r^ and s. Multiple linear regression equation was fitted using average weekly egg production per bird as dependent variable and weekly temperature and humidity as explanatory variable to study the impact of climatological parameters on egg production in quails. The investigation has the following, salient features. (i) The hatching weight of Japanese quails were 7.1369 g. (ii) The females weighed more than the males during the entire period of experiment and the body weights have shown an increasing trend. At the end of 12th week the average body weights of males and females were 157.6552 g and 179.2500 g respectively. (iii) Rao's method justified that initial body weights • had no significant effect on growth rate. • (iv) Gompertz curve = a exp [-b exp(-kt)'] was most , suitable for , ascertaining growth in quails on individual basis as well as on the basis of • average body weights over twelve weeks. (v) Average age at sexual maturity (females) was found to be approximately 10 weeks and on an average the eggs weighed 12.20 g. (vi) Quadratic function in logarithmic scale ; = a f b(logJ^) + c(log^)^ was most suitable , for ascertaining egg production in quails (weekly, , fortnightly, hen housed and hen day production • basis). (vii) Climatic parameters had significant impact on egg production in quails.ThesisItem Open Access Clustering genotypes based on G x E interaction in the absence of homogenecity of error variances(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 1992) Chandrika, C; KAU; Gopinathan Unnithan, V KA distance function between every pair of genotypes which measures the genotype-environment interaction in the case of heterogeneity of error variances in different environments was derived herein. A dissimilarity index for any set of genotypes which also measures the within group genotype-environment interaction sum of squares in terms of the pairwise distance function was also derived. Two methods of clustering, viz., statistical clustering and clustering by minimisation of average within cluster genotype-environment interaction making use of the proposed dissimilarity index were also proposed. Statistical clustering helps to group the genotypes such that genotype-environment interaction within any group is insignificant while any addition to the cluster makes it significant. In other words the idea of statistical clustering is to identify genotypes having similar response to varying environments. A point to be noted is that all the groups formed by statistical clustering may not be non overlapping. The other procedure helps to form optimum clustering by minimising the average within cluster genotype-environment interaction using an. iterative relocation algorithm. These clustering procedures were illustraited making use of two sets of data.ThesisItem Open Access Comparative study of lactation curves in goats(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 1991) Anita, S; KAU; George, K CBased on the weekly milk yield data of 20 weeks duration over different parities of the seven yenetic groups viz. Alpine Malabari, Malabari, Saanen Malabari, F2A , F2S, F3A and F3S maintained at the KAU, Goat Farm during the period 1976-'87, the following objectives were investigated. 1. To fit various lactation curve models in different breeds of goats and to select the most suitable one 2. To suggest a procedure for predicting complete lactation yield using various part lactation yields, 3. To study the effect of genetic and non-genetic factors on milk production traits. 4. To compare the persistency of milk yield among the selected breeds. On the basis of the criterions I, r and s eleven types of fitted lactation curves were compared. Among the curves compared the quadratic-cum-log and linear hyperbolic functions were selected as the best two curves for the genetic groups,Alpine Malabari, Malabari, F2A, F2S, F^A while for genetic groups Saanen Malabari and F^S the linear hyperbolic and quadratic log scale functions were the best two selected curves. As the linear hyperbolic function was found to be suited for all breeds under study it was selected as the best fitted curve for goats. Taking various cumulative part records of 4, 8 and12 weeks the linear hyperbolic function was then fitted to the parity-wise and pooled data of the seven genetic groups. It revealed that efficiency of over 98 per cent was achieved for all the part records though the efficiency increases with each added part record and hence this function could be selected as a prediction equation for the prediction of total yield from part record. Based on the ANOVA obtained by a two way classified non orthogonal data analysis the breed, order of lactation and their interaction were found to have significant influence on average yield. Among the breeds Saanen Malabari and among the parities fourth parity were found to be significantly different from the others and have the highest average weekly yield. Among the four methods used for comparing the seven genetic groups by calculating the persistency index, three methods (except method II) gave Saanen Malabari as the highest persistent one. By method II the highest index was attained by F^S followed by Saanen Malabari. Since Saanen Malabari gave the highest yield for pooled and individual parity data it was selected as the most persistent and high yielding breed.ThesisItem Open Access Pooled analysis of dependent sets of data(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 1991) Sukumaran, K; KAU; Gopinathan Unnithan, V KA new methodology for the analysis of data generated from experiments in which observations constitute repeated measurements from the same experimental unit at different points of time was developed. The problem of dependence of error terms in successive observations was taken care of in the model for analysis itself. The model included regression of error terms on those in the yester years/seasons. The error mean square from this model was derived using principle of least squares. The proposed method was compared with the widely adopted split-plot analysis and its superiority discussed. The method was illustrated using data generated from an experiment conducted to compare three varieties of alfalfa laid out in RBD with six replications and observations taken in four consecutive seasons. The superiority of the new method over the split-plot analysis was evident in the example considered.ThesisItem Open Access Development of a suitable model for ascertaining the growth and egg production in quails(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 1991) John Thomas, M; KAU; George, K CAn investigation was carried out into the growth and egg production aspect of Japanese quails at the Kerala Agricultural University Poultry Farm, Mannuthy on 1st February, 1989 with the following objectives. 1. t.o find a suitable relationship between age and body weight. 2. to investigate the trend of egg production i n quails through suitable mathematical models. 3. to study the impact of climate parameters (temperature, humidity) on egg production in quails The birds were reared under uniform feed formula and I identical management practices (recommended by Kerala Agricultural University Package ;of Practices). The investigation mainly depended on data consisting of weekly body weights of individual birds, daily egg production of birds (beginning from age at sexual maturity) and daily climatological parameters (temperature and humidity) from beginning till the end of experiment of 30th September, 1989. Mathematical models such as linear, quadratic, exponential, Von-Bertalanffy, modified exponential, logistic and Gompertz were fitted for the purpose using body weights of individual birds as well as average body weights over twelve weeks and the fitted models were compared using coefficient of determination (r^) and standard error of estimate(s). Mathematical models such as linear, exponential, parabolic exponential, inverse polynomial, Gamma function, Gamma-type functicn, quadratic function, quadratic function in logarithmic scale, quadratic-cum-log, emperical and linear hyperbolic functions were fitted for the development of suitable models for ascertaining egg production using total weekly, fortnightly egg production, hen housed and hen day egg production and fitted models were compared using Furnival . 2 index, r and s. Multiple linear regression equation was fitted using average weekly egg production per bird as dependent variable and weekly temperature and humidity as explanatory variable to study the impact of diimatological parameters on egg production in quails.ThesisItem Open Access Influence of weather parameters on the yield of black pepper(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 1990) Dessy Mabel; KAU; Gopinathan Unnithan, V KInfluence of weather parameters on the yield of black pepper was studied utilising the data on yield of 29 varieties of pepper (Pipger nigrum) and maximum temperature, minimum temperature, relative humidity, rainfall and number of rainy days recorded from 1963-64 to 1979-80 at The Pepper Research Station, Kerala Agricultural University, Panniyoor, in the Cannanore District of Kerala. Averages/totals of weather elements for standard weeks as well as for fortnights during the critical period of crop growth viz, from April 9 to August 12 were determined. Correlation coefficients of all the weather elements of standard weeks and fortnights with annual yield when represented in correlograms revealed, wide variations in response of different varieties to changes in climatic factors among the 29 varieties. In other wards there was definite evidence of genotype - environment interaction. Forcasting models, based on weekly as well as fortnightly weather elements were estimated for each of the 29 varieties of black pepper by two stage linear regression technique. First stage models were estimated by multiple linear regression and the second stage models were estimated with the estimates of yield from first stage models as explanatory variables by step-wise regression technique. The forecasting models utilising weekly climatic data had higher predictability compared to that utilising fortnightly data. All the final forecasting models with weekly data had predictability of 98% and above. More over the first stage models, from weekly data, could also be used to forecast yield of all varieties of black pepper with remarkable accuracy.ThesisItem Open Access Statistical investigations on the analysis of data of long term manurial trials on paddy(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 1990) Rani John, V; KAU; Prabhakaran, P VThe suitability of different statistical techniques for the analysis of data of long term fertiliser trials was examined with the help of secondary data gathered from the permanent manurial experiment in paddy at Regional Agricultural Research station. Pattambi and certain new methods with distinct advantages over the existing methods were suggested for the same. The relative efficiencies of various mathematical functions in representing the yield-fertiliser relationship and in estimating the optimum level of the applied nutrient were also evaluated on the basis of secondary data gathered from the various fertiliser experiments on paddy conducted at the various rice research stations under the KAU during the last ton years. Two new mathematical.functions were also developed to represent toe response pattern for certain types of trivial data. The methods evaluated for the analysis of data of long term trials include method of groups of experiments split plot analysis* principal component analysis non parametric method proposed by Rai and Rao stability analysis proposed by Eberhart and Russell.Iran parametric stability analysis proposed by Kassar and Kuhn and analysis based on principle of game theory. A new non parametric method as an extension of Friedman's two way analysis of variance by ranks was also developed for the analysis of such data. This method was found to be almost as powerful as the method proposed by Rai and Rao and hence can be regarded as on improvement over the existing methods as it is free from any stringent assumptions on the nature of the underlying universe. Principal component analysis was also found to be empirically atleast as efficient as tho method of groups of experiments/split plot analysis and can be adjudged to be a bettor alternative to the solution of the same problem on the grounds of theoretical and statistical validity.ThesisItem Open Access Comparison of alternate methods for the control of experimental error in perennial crops(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 1994) Seena, C; KAU; Prabhakaran, P VThe feasibility of using certain novel devices for the control of error in experiments on perennial crops was examined on the basis of actual experimental data and the resulting efficiency gain evaluated. A considerable amount of reduction in error variance was achieved by the application of analysis of covariance with suitable functions of pre-experimental yield as concomitant variable. Application of quadratic covariance resulted a substantial gain of precision in the analysis of data on coconut. Nearest neighbourhood analysis (NNA) resulted in a significant improvement of precision in the analysis of data in most of the experiments. Double covariance analysis involving suitable functions of pre-experimental yield and NN variable as covariates resulted in further reduction of experimental error. Pearce’s iterative NN procedure was found to be the best alternative method for reduction of error over the coventional method of stratification. A plot of eight trees was found to be optimum for conducting yield trails on coconut and cashew. The percentage of genetic variability to the total phenotypic variability in the yields of cashew, coconut and cocoa was estimated to be 77.7, 83.4 and 45.4 respectively. The result called for the use of calibration of the plots and choice of appropriate concomitant variables for the reduction of experimental error in designing experiments on perennial crops.ThesisItem Open Access Analysis of auto correlated data in groups of experiments(Department of Agricultural Statistics, College of Horticulture, Vellanikkara, 1994) Premi, T C; KAU; Gopinathan Unnithan, V KAnalysis of variance model for the groups of experiments needs modification, when observations are taken repeatedly on the same experimental units owing to the autocorrelated nature of error terms. A model which takes the dependence of error terms into consideration was evolved for dealing such situations. But estimation of parameters using least square principle and their tests of significance not straight forward. Therefore numerical solutions using iterative technique was employed for estimation of parameters of the model. The newly developed procedure was compared to the widely used analysis of the split-plot setup and the comparative advantage of the new method was established. The new methodology along with the widely used analysis of the split – plot set up were illustrated using two different sets of data. The superiority of the new method over the split –plot analysis was demonstrated in both sets of data.
